- Research areas
Born in Naples, Roberto is currently a researcher in Leonardo’s artificial intelligence team, where he is actively involved in the HPC management, AI and Big Data stream of research. Specifically, his projects relate to the development of AI algorithm for anomaly detection applications. He is also involved in the data lake setup for the storage and processing of the data related to the company business.
Since joining Leonardo in January 2021, Roberto has continued collaborating with INFN (Bologna) to pursue his Ph.D in Data Science & Computation. The thesis’s main topic is related to the high energy physics anomaly detection for Beyond Standard Model searches. This activity aims to support the ATLAS collaboration analysis and is mainly focused on unsupervised methods like Variational Autoencoder for model-independent searches and data-driven approaches. Other research interests regard deep learning computer vision techniques applied to the biomedical images used to support Bologna’s Physiology department for microscopic biological images analysis. Due to the pandemic crisis, Roberto is also actively involved in the COVID-19 forecasting task force to support Emilia-Romagna hospitals management.
Roberto graduated in Physics at the University of Bologna in 2017 (full mark with Laude). During his master’s thesis, he was involved in finite-element simulation analysis to study carbon nanotubes properties inside the alumina nanoporous matrix in collaboration with I.N.F.N and C.N.R (Bologna). Subsequently, he refined his study, attending a master in financial mathematics and working in C.R.I.F S.p.a in the Big Data and Analytics team during his industrial experience.
Automating cell counting in fluorescent microscopy through deep learning with c-ResUnet
R Morelli et al. - Scientific Reports, 25-11-2021
Distributed workflows with Jupyte; Iacopo Colonnelli, Marco Aldinucci, Barbara Cantalupo, Luca Padovani, Sergio Rabellino, Concetto Spampinato, Roberto Morelli, Rosario Di Carlo, Nicolò Magini, Carlo Cavazzoni; Future Generation Computer Systems; 2022
Contribution to: "Uncovered signatures + Run 3 opportunities workshop":
Variational Autoencoder studies in SUSY; (A. Cervelli, R. Morelli)
Participation in: Anomaly Detection Mini-Workshop LHC-Summer Olympics 2020